activity
20202022
most citedSimultaneous Human-robot Matching and Routing for Multi-robot Tour Guiding under Time Uncertainty

6 citations · 14 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO20225 cited

Learning Task Requirements and Agent Capabilities for Multi-agent Task Allocation

Bo Fu, William Smith, Denise Rizzo +3

This paper presents a learning framework to estimate an agent capability and task requirement model for multi-agent task allocation. With a set of team configurations and the corre…

cs.RO20226 cited

Simultaneous Human-robot Matching and Routing for Multi-robot Tour Guiding under Time Uncertainty

Bo Fu, Tribhi Kathuria, Denise Rizzo +4

This work presents a framework for multi-robot tour guidance in a partially known environment with uncertainty, such as a museum. In the proposed centralized multi-robot planner, a…

eess.SY20223 cited

Sensitivity analysis of a mean-value exergy-based internal combustion engine model

Gabriele Pozzato, Denise Rizzo, Simona Onori

In this work, we conduct a sensitivity analysis of the mean-value internal combustion engine exergy-based model, recently developed by the authors, with respect to different drivin…

eess.SY2021

Exergy-based modeling framework for hybrid and electric ground vehicles

Federico Dettù, Gabriele Pozzato, Denise M. Rizzo +1

Exergy, or availability, is a thermodynamic concept representing the useful work that can be extracted from a system evolving from a given state to a reference state. It is also a…

eess.SY2021

Safe Learning Reference Governor: Theory and Application to Fuel Truck Rollover Avoidance

Kaiwen Liu, Nan Li, Ilya Kolmanovsky +2

This paper proposes a learning reference governor (LRG) approach to enforce state and control constraints in systems for which an accurate model is unavailable, and this approach e…

cs.RO2020

Heterogeneous Vehicle Routing and Teaming with Gaussian Distributed Energy Uncertainty

Bo Fu, William Smith, Denise Rizzo +2

For robot swarms operating on complex missions in an uncertain environment, it is important that the decision-making algorithm considers both heterogeneity and uncertainty. This pa…